The BeiDou Navigation Satellite System (BDS) is a global satellite navigation system that was independently developed by China. It is the fourth mature satellite navigation system following the global positioning system (GPS) of the United States, the GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS) of Russia and the Galileo Satellite Navigation System of Europe.
The BeiDou Navigation Satellite System consists of a space segment, a ground segment and a user segment, wherein the space segment is designed to consist of 5 Geosynchronous Earth Orbit satellites and 30 non-Geosynchronous Earth Orbit satellites. The BDS can currently provide to various users locating, navigation and time services with a high precision and a high reliability in an all-weather and all-time manner in the Asia-Pacific area, and has the capacity of short-message communication. Currently the locating precision is 10 meters, the velocity measurement precision is 0.2 meters/second, and the time service precision is 10 nanoseconds.
The differences between BDS and GPS are:
1. The BDS possesses both of locating and communication functions. If the system starts the service, the receivers can directly communicate via the navigation satellites, without the supporting by other communication systems. However, GPS can only locate.
2. Because the BeiDou System currently merely covers China and the neighboring countries and regions, it does not have a communication dead zone in design.
3. The BeiDou System is of active locating, which requires the clients to send information to the satellites. Accordingly it provides selective services, and can at any time decide whether to provide the locating service to a certain client. However, the GPS system is of passive locating, and cannot restrict undesirable users from using it (unless the entire system is shut). Therefore, the BDS satellites can locate only after receiving client information and responding, and if the users are too many clog may happen, while the GPS system can provide locating information simultaneously to an infinite quantity of receivers.
Advanced Receiver Autonomous Integrity Monitoring (ARAIM), as a new generation of integrity monitoring technology of airborne receivers of satellite navigation, has the capacity of using multiple GNSS (Global Navigation Satellite System) constellations and bifrequency and multiple-fault monitoring, can support vertical navigation below the 200-feet height (LPV-200), has a low upgrading cost and obvious performance improvement, and is currently a research hotspot in the field of application in civil aviation of the GNSS. The benchmark algorithm of the ARAIM is using the data transmitted by the satellite navigation system as the input, performing navigational locating and integrity assessment by using the ephemeris broadcast by the satellites, and correspondingly outputting indicators that characterize the precision and the integrity of a target location such as protection class, precision and usability. For the ARAIM, as a technique of integrity monitoring, it is very important how to ensure its integrity indicator and output in real time its usability.
Fault detection refers to a navigation receiver detecting whether the received satellite navigation signal has an abnormal deviation. When the navigation receiver has received a redundant observed quantity besides the measurement values necessary for the locating, it judges whether the redundant observed quantity and all of the observed quantities used for the detection are consistent, thereby judging whether a fault exists. An ARAIM receiver performs autonomous fault detection by using such a principle, to ensure the aviation operation safety.
The purpose of the fault detection is to ensure that when a satellite cannot correctly emit a navigation signal a receiver can in time emit an alarm, thereby ensuring the safety and reliability of the navigation service. The basic idea of fault detection is performing consistency check to test statistics by using redundant information. Currently, according to the difference between the test statistics of the fault detection, all of the methods of ARAIM fault detection can be classified into two classes: method of location domain and method of pseudo-range domain. The substantial detection method of the ARAIM is the solution separation algorithm of the pseudo-range domain, which achieves fault detection by comparing the test statistics and a threshold. Assuming that a certain satellite has a fault, the subset locating solution including the fault satellite must separate from subset locating solutions including merely healthy satellites, so the fault is found.
However, in the solution separation algorithm, each time of hypothesis testing performs one time of locating resolving, and finally test statistics of the same quantity as the quantity of fault hypothesis will be generated. Because the fault detection is performed on the airborne receiver, the large amount of resolving definitely affects the real-time capability. As the quantity of the visible satellites received by receivers is increasing, the quantities of observed quantities and fault modes increase accordingly, and the problem of the massive calculation that the solution separation algorithm is facing is required to be solve urgently.
Integrity refers to the capacity of a navigation system of in time giving an alarm when the locating information provided by the navigation system cannot satisfy the requirements of operation due to a certain fault. The core indicators of integrity include alarming time, alarming threshold and integrity risk probability value. When a satellite navigation system cannot satisfy the requirements of navigation operation, that can be solved by the autonomous fault detection of the receiver. However, fault detection may have omission, which results in that there is no alarm when the locating error exceeds the alarming threshold, when an integrity risk emerges, which affects the integrity of the entire ARAIM service. The locating information when an integrity risk is happening is referred to as Hazardously Misleading Information (HMI), and the integrity risk is determined by using the probability of the occurrence of the Hazardously Misleading Information.
In the ARAIM, as a multi-constellation satellite navigation system, besides the commonly seen satellite faults such as single satellite or multiple satellites, constellation faults are also required to be considered. Constellation faults are faults that are caused by the space segment or the ground segment and have correlation. Such types of faults affect the navigation signals or texts of multiple satellites, which results in that all of the pseudo-range measurement values of the satellites in the navigation constellation maintain consistent, and do not have a redundant observed quantity, so the solution separation algorithm cannot be used for the consistency detection. Constellation faults cause receivers to obtain pseudo-range measurement values that are consistent, lack the comparison of redundant observed quantities, and not be able to perform fault detection by using the autonomous detection of the receivers.
Therefore, in order to solve, in the prior art, the problem of real-time capability of the solution separation algorithm, and the problem of the unavailability under constellation faults, the present disclosure provides a method for ARAIM fault detection based on extraction of characteristic value of pseudo-range measurement.